To recognize a rotated image pattern, a prior art system generally requires large memory space and or long processing time. This is because the recognition is usually accomplished in real time and the image pattern may be reduced, enlarged or rotated. Any combination of these factors further complicates the processing time and memory space requirements and tends to lower accuracy in correctly recognizing an image pattern.
Prior art attempts include the use of the Zernike Moment in recognizing an image pattern. For example, Japanese Laid Patent Publication Hei 9-147109 (Application Serial Number Hei 7-301250) discloses the reduced memory requirement in recognizing a predetermined image pattern based upon the use of a radial polynomial table containing intermediate values for determining Zernike Moment values. The Zernike Moment values are defined as a product of a radial polynomial value and a pixel value. Although a size difference of the predetermined image pattern is accommodated by adjusting the radial polynomial table values, a rotated image pattern as shown in FIG. 1 is not recognized according to the disclosure. This is because the Zernike Moment values for a predetermined image pattern are constant over the rotational angle of the image.
In order to recognize a predetermined image pattern which is rotated at an arbitrary angle, prior art attempts such as Japanese Laid Patent Publication Hei 8-279021 (Application Serial Number Hei 7-301250) disclose that a rotational angle of a predetermined image pattern is determined based upon a characteristic value such as a number of "on" pixels at equidistant locations from a common point. The measure characteristic value is compared to a set of standard dictionary values each for a known angle, and a rotational angle is selected according to minimal distance to the standard characteristic value. However, this prior art attempt requires additional processing for higher degree characteristic values as well as the number of comparisons.